Get Data
library(palmerpenguins)
data("penguins")
Replay The Data Set (May Not Look So Great)
## # A tibble: 344 x 7
## species island culmen_length_mm culmen_depth_mm flipper_length_… body_mass_g
## <fct> <fct> <dbl> <dbl> <int> <int>
## 1 Adelie Torge… 39.1 18.7 181 3750
## 2 Adelie Torge… 39.5 17.4 186 3800
## 3 Adelie Torge… 40.3 18 195 3250
## 4 Adelie Torge… NA NA NA NA
## 5 Adelie Torge… 36.7 19.3 193 3450
## 6 Adelie Torge… 39.3 20.6 190 3650
## 7 Adelie Torge… 38.9 17.8 181 3625
## 8 Adelie Torge… 39.2 19.6 195 4675
## 9 Adelie Torge… 34.1 18.1 193 3475
## 10 Adelie Torge… 42 20.2 190 4250
## # … with 334 more rows, and 1 more variable: sex <fct>
Descriptive Statistics
# summary(penguins)
# psych gives a good list of descriptive statistics
psych::describe(penguins)
## vars n mean sd median trimmed mad min max
## species* 1 344 1.92 0.89 2.00 1.90 1.48 1.0 3.0
## island* 2 344 1.66 0.73 2.00 1.58 1.48 1.0 3.0
## culmen_length_mm 3 342 43.92 5.46 44.45 43.91 7.04 32.1 59.6
## culmen_depth_mm 4 342 17.15 1.97 17.30 17.17 2.22 13.1 21.5
## flipper_length_mm 5 342 200.92 14.06 197.00 200.34 16.31 172.0 231.0
## body_mass_g 6 342 4201.75 801.95 4050.00 4154.01 889.56 2700.0 6300.0
## sex* 7 333 1.50 0.50 2.00 1.51 0.00 1.0 2.0
## range skew kurtosis se
## species* 2.0 0.16 -1.73 0.05
## island* 2.0 0.61 -0.91 0.04
## culmen_length_mm 27.5 0.05 -0.89 0.30
## culmen_depth_mm 8.4 -0.14 -0.92 0.11
## flipper_length_mm 59.0 0.34 -1.00 0.76
## body_mass_g 3600.0 0.47 -0.74 43.36
## sex* 1.0 -0.02 -2.01 0.03
Only Look At A Subset of Variables
mynewdata <- subset(penguins, select = c(species,
island,
body_mass_g))
pander(psych::describe(mynewdata))
Table continues below
| species* |
1 |
344 |
1.919 |
0.8933 |
2 |
1.899 |
1.483 |
| island* |
2 |
344 |
1.663 |
0.7262 |
2 |
1.58 |
1.483 |
| body_mass_g |
3 |
342 |
4202 |
802 |
4050 |
4154 |
889.6 |
| species* |
1 |
3 |
2 |
0.1591 |
-1.732 |
0.04816 |
| island* |
1 |
3 |
2 |
0.6086 |
-0.9064 |
0.03915 |
| body_mass_g |
2700 |
6300 |
3600 |
0.4662 |
-0.7395 |
43.36 |